LEADER 03036nam 22004813 450 001 9911019510703321 005 20250430221013.0 010 $a9781394171897 010 $a9781394171910 035 $a(MiAaPQ)EBC30786531 035 $a(CKB)28495736400041 035 $a(Au-PeEL)EBL30786531 035 $a(Exl-AI)30786531 035 $a(OCoLC)1403973244 035 $a(EXLCZ)9928495736400041 100 $a20231016d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAccelerators for Convolutional Neural Networks 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2023. 210 4$dİ2024. 215 $a1 online resource (307 pages) 311 08$a9781394171880 327 $aCover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- Part I Overview -- Chapter 1 Introduction -- 1.1 History and Applications -- 1.2 Pitfalls of High?Accuracy DNNs/CNNs -- 1.2.1 Compute and Energy Bottleneck -- 1.2.2 Sparsity Considerations -- 1.3 Chapter Summary -- Chapter 2 Overview of Convolutional Neural Networks -- 2.1 Deep Neural Network Architecture -- 2.2 Convolutional Neural Network Architecture -- 2.2.1 Data Preparation -- 2.2.2 Building Blocks of CNNs -- 2.2.2.1 Convolutional Layers -- 2.2.2.2 Pooling Layers -- 2.2.2.3 Fully Connected Layers -- 2.2.3 Parameters of CNNs -- 2.2.4 Hyperparameters of CNNs -- 2.2.4.1 Hyperparameters Related to Network Structure -- 2.2.4.2 Hyperparameters Related to Training -- 2.2.4.3 Hyperparameter Tuning -- 2.3 Popular CNN Models -- 2.3.1 AlexNet -- 2.3.2 VGGNet -- 2.3.3 GoogleNet$7Generated by AI. 330 $aThis book provides an in-depth exploration of accelerators for convolutional neural networks (CNNs), a pivotal component in the field of artificial intelligence and computer vision. It covers the architecture of CNNs, compressive coding techniques, and the design of both dense and sparse CNN accelerators. The text discusses hardware and software co-design and scheduling strategies to optimize CNN performance. Aimed at students, researchers, and professionals in computer architecture and hardware design, the book serves as a comprehensive reference on the development and implementation of CNN accelerators.$7Generated by AI. 606 $aNeural networks (Computer science)$7Generated by AI 606 $aComputer architecture$7Generated by AI 615 0$aNeural networks (Computer science) 615 0$aComputer architecture 676 $a006.32 700 $aMunir$b Arslan$0848010 701 $aKong$b Joonho$01839620 701 $aQureshi$b Mahmood Azhar$01839621 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9911019510703321 996 $aAccelerators for Convolutional Neural Networks$94418898 997 $aUNINA